Self training-based methods have been successful in unsupervised and semi-supervised domain adaptive works [1]}, [2]}, [3]}, but rely on confidence thresholding to filter noisy pseudo-labels. As illustrated in the example from Figure REF , the use of high thresholds (as is general practice) results in training the model on easy samples and incorrect labels of high confidence that contribute to the enforcement of errors during adaptation.
